Improved deformation reconstruction of composite material structures based on optical fiber sensing

Due to high strength and lightweight, composite material structures have been widely used in various industries such as aerospace, automotive, civil engineering, and healthcare. Real-time deformation monitoring based on optical fiber sensing technology holds immense potential in composite materials' structural health monitoring (SHM). In this study, structural deformation reconstruction algorithms have been investigated by improving the slope recursion algorithm and the Ko displacement theory. The slope recursion algorithm is enhanced through angle averaging. Cross-validation is employed to increase strain-fitting accuracy for the Ko displacement theory. Finite element simulation analysis and deformation reconstruction experiments of a carbon fiber composite plate were conducted to validate the deformation reconstruction algorithms. Fiber Bragg grating (FBG) sensors were applied to measure quasi-distributed strain as inputs for the algorithms. The results show that the overall reconstruction accuracy increased by 1.91% with the improved slope method and by 0.92% with the optimized Ko displacement theory. Deformation reconstruction experiments of a composite material reinforced structure were carried out, and 70 FBG sensors were installed on its surface for strain field measurement. The experimental results indicate the feasibility of the proposed deformation reconstruction methods for complex structures.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-11-27
DOI
https://doi.org/10.1038/s41598-025-26592-y
Primary Topic
Advanced Fiber Optic Sensors
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improved deformation reconstruction of composite material structures based on optical fiber sensing

Ruiya Li, Qiufeng Huang, Sheng Yin, Yuwei Sun et al.
Scientific Reports
Advanced Fiber Optic Sensors
article

Improved deformation reconstruction of composite material structures based on optical fiber sensing

Ruiya Li, Qiufeng Huang, Sheng Yin, Yuwei Sun, Dongsheng Zhang, Quan Liu, Peng Yu, Jun Huang, Zimin Peng
article en

Abstract

Due to high strength and lightweight, composite material structures have been widely used in various industries such as aerospace, automotive, civil engineering, and healthcare. Real-time deformation monitoring based on optical fiber sensing technology holds immense potential in composite materials' structural health monitoring (SHM). In this study, structural deformation reconstruction algorithms have been investigated by improving the slope recursion algorithm and the Ko displacement theory. The slope recursion algorithm is enhanced through angle averaging. Cross-validation is employed to increase strain-fitting accuracy for the Ko displacement theory. Finite element simulation analysis and deformation reconstruction experiments of a carbon fiber composite plate were conducted to validate the deformation reconstruction algorithms. Fiber Bragg grating (FBG) sensors were applied to measure quasi-distributed strain as inputs for the algorithms. The results show that the overall reconstruction accuracy increased by 1.91% with the improved slope method and by 0.92% with the optimized Ko displacement theory. Deformation reconstruction experiments of a composite material reinforced structure were carried out, and 70 FBG sensors were installed on its surface for strain field measurement. The experimental results indicate the feasibility of the proposed deformation reconstruction methods for complex structures.

Scientific ReportsVol. 15(1)
Wuhan University of Technology (CN), Wuhan University (CN), Shanghai Institute of Measurement and Testing Technology (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 63%
Advanced Fiber Optic Sensors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.